Long-term changes of phytoplankton community by water sampling method in Xiagu Sea waters of Xiamen, China, were investigated in this study. Species composition of the phytoplankton community in these waters changed greatly since the 1950s. The numbers of Dinophyta species increased significantly, although Bacillariophyta species are generally dominant. The succession of dominant species in phytoplankton community is obvious:large-size dominant species such as Biddulphia sinensis of the 1950s were gradually replaced by small-size ones such as Cyclotella striata and Nitzschia closterium, and species that still maintain dominant such as Skeletonema costatum are also small ones, leading the whole phytoplankton community of smaller size. Cell density of phytoplankton community increased greatly, among which cell density of the most dominant species Skeletonema costatum have been increasing in exponent function. Margalef index of phytoplankton community decreased, indicating decline of biodiversity of the community, and dominant character of Skeletonema costatum increased. Generally, the structure of the entire phytoplankton community is becoming more and more singular and unstable, which makes the occurrence of red tides more frequent. The succession in the phytoplankton community is related to the long-term changes in marine environment, influenced by human activities and global climate changes, especially the increases of nutrient content.
Three kind of application of ADCP is reported for long-term monitoring in coastal sea.(1)The rourine monitoring of water qualities.The water quality and ADCP echo data (600 kHz) observed in the long-term are analgzed at MT (Marine Tower) Station of Kansai International Airport in the Osaka Bay,Japan.The correlation between the turbidity and echo intensity in the surface layer is not good because air bubbles generated by breaking wave are not detected by the turbidity meter,but detected well by ADCP.When estimating the turbidity consists of plankton population from echo intensity,the effect of bubbles have to be eliminated.(2) Monitoring stirring up of bottom sediment.The special observation was carded out by using following two ADCP in the Osaka Bay,One ADCP was installed upward on the sea.The other ADCP was hanged downward at the gate type stand about 3 m above from the bottom.At the spring tide,high echo intensities indicating the stirring up of bottom sediment were observed.(3) The monitoring for the boundary condition of water mixing at an estuary.In summer season,the ADCP was set at the mouth of Tanabe Bay in Wakayama Prefecture,Japan.During the observation,water temperature near the bottom showed remarkable falls with interval of about 5~7 d.When the bottom temperature fell,the inflow current with low echo intensity water appears at the bottom layer in the ADCP record.It is concluded that when occasional weak northeast wind makes weak coastal upwelling at the mouth of the bay,the combination of upwelling with internal tidal flow causes remarkable water exchange and dispels the red tide.
From the analyses of the satellite altimeter Maps of Sea Level Anomaly (MSLA) data, tidal gauge sea level data and historical sea level data, this paper investigates the long-term sea level variability in the East China Sea (ECS). Based on the correlation analysis, we calculate the correlation coefficient between tidal gauge and the closest MSLA grid point, then generate the map of correlation coefficient of the entire ECS. The results show that the satellite altimeter MSLA data is effective to observe coastal sea level variability. An important finding is that from map of correlation coefficient we can identify the Kuroshio. The existence of Kuroshio decreases the correlation between coastal and the Pacific sea level. Kurishio likes a barrier or a wall, which blocks the effect of the Pacific and the global change. Moreover, coastal sea level in the ECS is mainly associated with local systems rather than global change. In order to calculate the long-term sea level variability trend, the empirical mode decomposition (EMD) method is applied to derive the trend on each MSLA grid point in the entire ECS. According to the 2-D distribution of the trend and rising rate, the sea level on the right side of the axis of Kuroshio rise faster than in its left side. This result supports the barrier effect of Kuroshio in the ECS. For the entire ECS, the average sea level rose 45.0 mm between 1993 and 2010, with a rising rate of (2.5±0.4) mm/a which is slower than global average. The relatively slower sea level rising rate further proves that sea level rise in the ECS has less response to global change due to its own local system effect.
Water waves, wave-induced long-shore currents and movement of pollutants in waves and currents have been numerically studied based on the hyperbolic mild-slope equation, the shallow water equation, as well as the pollutant movement equation, and the numerical results have also been validated by experimental data. It is shown that the long-shore current velocity and wave set-up increase with the increasing incident wave amplitude and slope steepness of the shore plane; the wave set-up increases with the increasing incident wave period;and the pollutant morement proceeds more quiekly with the increasing incident wave amplitude and slope steepness of the shore palane. In surf zones, the long-shore currents induced by the inclined incident waves have effectively affected the pollutant movement.
Seasonal variation and topography of the mixed layer in the Sea of Japan are studied by comparison of results from long-term observation data analysis and from numerical simulation with the MHI oceanic model (Shapiro.1998.Marine Hydrophysical Journal,6:26~40).The data are retrieved from Oceanographic Atlas of the Bering Sea,Okhotsk Sea,and Japan/East Sea (Rostov,Rostov,Dmitrieva,et al.2003.Pacific Oceanography,1(1):70~72).The simulated and long-term patterns are compared.An impact of surface buoyancy flux,wind,and convergence/divergence of surface currents upon the mixed layer in the Sea of Japan is analyzed.
By analysing the scatter diagrams of characteristic the wave height H and the period T on the basis of instrumental data from various ocean wave stations, we found that the conditional expectation and standard deviation of wave period for a given wave height can be better predicted by using the equations of normal linear regression rather than by those based on the lognormal law.The latter was implied in Ochi's bivariate log-normal model (Ochi.1978) for the long-term joint distribution of H and T.With the expectation and standard deviation predicted by the normal linear regression equations and applying proper types of distribution, we have obtained the conditional distribution of T for given H.Then combining this conditional P (T/H) with long-term marginal distribution of the wave height P (H) we establish a new parameterized model for the long-term joint distribution P (H, T).As an example of the application of the new model we give a method for estimating wave period associated with an extreme wave height.
The global surface temperature change since the mid-19th century has caused general concern and intensive study. However, long-term changes in the marginal seas, including the seas east of China, are not well understood because long-term observations are sparse and, even when they exist, they are over limited areas. Preliminary results on the long-term variability of sea surface temperature (SST) in summer and winter in the seas east of China during the period of 1957-2001 are reported using the Ocean Science Database of Institute of Oceanology, Chinese Academy of Sciences, the coastal hydrological station in situ and satellite data. The results show well-defined warming trends in the study area. However warming and cooling trends vary from decade to decade, with steady and rapid warming trends after the 1980s and complicated spatial patterns. The distribution of SST variation is intricate and more blurred in the areas far away from the Kuroshio system. Both historical and satellite data sets show significant warming trends after 1985. The warming trends are larger and spread to wider areas in winter than in summer, which means decrease in the seasonal cycle of SST probably linked with recently observed increase of the tropical zooplankton species in the region. Spatial structures of the SST trends are roughly consistent with the circulation pattern especially in winter when the meridional SST gradients are larger, suggesting that a horizontal advection may play an important role in the long-term SST variability in winter.
It is of vital importance to reduce injuries and economic losses by accurate forecasts of typhoon tracks. A huge amount of typhoon observations have been accumulated by the meteorological department, however, they are yet to be adequately utilized. It is an effective method to employ machine learning to perform forecasts. A long short term memory (LSTM) neural network is trained based on the typhoon observations during 1949-2011 in China's Mainland, combined with big data and data mining technologies, and a forecast model based on machine learning for the prediction of typhoon tracks is developed. The results show that the employed algorithm produces desirable 6-24 h nowcasting of typhoon tracks with an improved precision.
The Chinese desert is one of the major sources of atmospheric mineral dust transported for a long distance to the North Pacific by the atmospheric circulation.The characteristic of the aerosol in the North Pacific is smilar to that of the aerosol in North China with a considerable concentration of mineral in spring due to the large-scale dust storm occurring in North China.The study of isotope tracer indicates that the concentration of Al is significantly related to 210Pb,suggesting that the mineral aerosol in the North Pacific may origir ate from the desert in Northwest China by using air mass trajectory analysis.About 6-12×106 tons of Chinese desert mineral dust per year would be transported to the North Pacific.
On the basis of maps of sea level anomalies data set from October 1992 to January 2004, pronounced low frequency variations with periods of about 500 d are detected in the area near 20°N from 160°W to 130°E. A linear two-layer model is employed to explain the mechanism. It is found that the first-mode long baroclinic Rossby waves at 20°N in the northwest Pacific propagate westward in the form of free waves at a speed of about 10.3 cm/s. This confirms that the observed low frequency variabilities appear as baroclinic Rossby waves. It further shows that these low frequency variabilities around 20°N in the northwest Pacific can potentially be predicted with a lead up to 900 d.